vidseeds-analytics

vidseeds-analytics is a skill for Claude Code, Codex from hashgraph-online/awesome-codex-plugins. It costs 58 tokens per session (890 once invoked), scanned A, original, Apache-2.0.

An analytics and research connection for YouTube channels and videos. It can retrieve channel data, inspect videos and transcripts, study competitors and trends, research keywords, and analyse comment sentiment.

In plain words
What is it for?
Use it for channel analytics, video diagnosis, channel intelligence, competitor research, breakout-video discovery, keyword research, captions, and author-voice analysis.
Why use it?
It brings channel and video evidence together so decisions are based on performance and audience information rather than guesses.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for channel analytics, video diagnosis, channel intelligence, competitor research, breakout-video…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hashgraph-online/awesome-codex-plugins/vidseeds-analytics
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add hashgraph-online/awesome-codex-plugins --skill vidseeds-analytics
Clone the repo
git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for vidseeds-analytics

README.md
[![agentmods](https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/vidseeds-analytics.svg)](https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/vidseeds-analytics)
Your own site
<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/vidseeds-analytics"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/vidseeds-analytics.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 890 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00058 $0.00890
Opus 5 $0.00029 $0.00445
Sonnet 5 $0.00012 $0.00178
Haiku 4.5 $0.00006 $0.00089

Measured yesterday against content hash 263943d82997, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

vidseeds-analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/CarrotGamesStudios/vidseeds-mcp/skills/vidseeds-analytics/SKILL.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analytics & intelligence (MCP)

Map the user's question to a tool - then read the tool description for inputs and seed cost.

YouTube account data

Goal Tool
Connected channels vidseeds_get_youtube_channels
Channel/video analytics vidseeds_get_youtube_analytics
Playlists vidseeds_get_channel_playlists
Transcript / captions vidseeds_get_youtube_video_transcript, vidseeds_get_youtube_video_captions

Channel intelligence (deep profile)

Goal Tool
Run analysis vidseeds_analyze_channel_intelligence
Poll status vidseeds_get_channel_intelligence_status
Read cached result vidseeds_get_channel_intelligence_cache
Narrative insights vidseeds_generate_channel_insights
Author voice vidseeds_analyze_author_voice

Pass channelId when multiple YouTube connections exist.

Single-video diagnosis

Goal Tool
Deep dive on one video vidseeds_analyze_video_autopsy
Best-practices check vidseeds_get_video_best_practices
Sponsor integrations vidseeds_scan_sponsor_integrations
Retention curve (simulated) vidseeds_simulate_retention_curve

Competitive & market context

Goal Tool
Compare channels vidseeds_compare_competitors
Outlier videos vidseeds_detect_outliers
Public channel audit vidseeds_audit_public_channel
Realtime anomalies vidseeds_get_realtime_anomalies

Read the full file on GitHub · 85 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 85 lines · 58 tokens per session scan A 263943d82997

Subscribe to this mod's changes

vidseeds-analytics is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (935 stars, last pushed today), licensed Apache-2.0. It adds 58 tokens to every session and 890 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.

Related

Other skills, from other repositories

search

Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.

taishi-i/awesome-ChatGPT-repositories · 57 tokens

sprr

Single PR reviewer for awesome-quant. Use when the user asks to review, validate, comment on, label, close, or merge one specific pull request that adds README.md entries. Triggers include "sprr", "review PR", "check PR", and "validate contribution".

wilsonfreitas/awesome-quant · 60 tokens

bprr

Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.

wilsonfreitas/awesome-quant · 61 tokens

drawio-reconstruction

Reconstructs reference images into high-fidelity, editable Draw.io files with rendered previews: native Draw.io elements carry text and structure, SVG covers simple icons that match the reference, and cropped or transparent PNGs preserve complex visuals. Use when the user wants a diagram image, research figure…

HKUSTDial/Supervisor-Skills · 102 tokens

benchmark-paper-template

Structures Benchmark and Evaluation papers using the five-pillar framework (Research Gap, Construction Pipeline, Evaluation Framework, Empirical Findings, optional Companion Method). Returns a completeness audit, a six-part Introduction logic chain, a Section 2-7 skeleton, and a pre-submission checklist. Use when…

HKUSTDial/Supervisor-Skills · 96 tokens

reverse-engineering-android-malware-with-jadx

Reverse engineers malicious Android APK files using JADX decompiler to analyze Java/Kotlin source code, identify malicious functionality including data theft, C2 communication, privilege escalation, and overlay attacks. Examines manifest permissions, receivers, services, and native libraries. Activates for requests…

adriannoes/awesome-agentic-ai · 82 tokens